AI gaming asset and player review analyzer for casino optimization

Abstract

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Description

[0001] This application claims priority from United States Provisional Patent Application No. 19 / 297,809, filed on 12 August 2025, the contents of which are to be taken as incorporated herein by reference. Copyright

[0002] A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyright rights whatsoever. Copyright 2025, LNW Gaming, Inc. Field

[0003] The present disclosure relates generally to system(s) and method(s) for operations associated with gaming and / or data analysis systems and, more specifically, to using artificial intelligence (AI) to analyze casino-related data. Background

[0004] Casino operators continuously strive to maximize revenue and enhance the overall experience for their patrons to encourage repeat business and increase time-on-device. A significant portion of revenue is derived from electronic gaming machines, often referred to as slot machines. The performance of these assets is highly dependent on factors such as their physical location on the casino floor, the game theme, the cabinet style, and various configurable parameters.

[0005] Currently, the process of optimizing the performance of these assets is often a manual and inefficient endeavor. Casino personnel typically download performance reports and manually analyze the data to identify which machines are underperforming. This process is not only timeconsuming but may also fail to uncover complex, non-obvious patterns in the data that could lead to more effective optimizations. Furthermore, a modern casino utilizes a multitude of disparate data systems to manage its operations. A significant challenge lies in organizing and analyzing data from all these sources cohesively, leading to missed opportunities for effective marketing 2026202226   07 Aug 2026 strategies. In addition, valuable insights from player reviews on social media are often missed and / or unused. Therefore, a need exists for an automated, intelligent solution that can overcome these limitations. Summary

[0006] An advantage of the present disclosure is to overcome, or at least ameliorate, at least one disadvantage of present arrangements.

[0007] One aspect of the present disclosure provides a method for optimizing casino operations using artificial intelligence, the method comprising: collecting, via a data collector module, raw data from a plurality of disparate data sources, wherein the data sources include a casino management system and an online platform; compiling, via a data compiler, the raw data into a structured format; training, via an artificial intelligence (AI) training module, an AI model using the structured data; analyzing, via an Asset Analyzer module utilizing the trained AI model, casino asset data to identify an optimization for a casino asset, wherein the optimization comprises one of a physical relocation of the asset or a parameter reconfiguration of the asset, wherein the casino asset is a multi-game multi-denomination (MGMD) machine, and the identified optimization is a recommendation to reconfigure a combination of games available on the MGMD machine; analyzing, via a Player Reviewer module utilizing the trained AI model, player review data from the online platform to determine a sentiment of the player review; and generating, for display on a unified dashboard, a first recommendation based on the identified optimization for the casino asset and a second recommendation based on the determined sentiment of the player review.

[0008] Another aspect of the present disclosure provides a system for optimizing casino operations, the system comprising: a processor; and a memory storing instructions that, when executed by the processor, cause the system to: collect raw data from a plurality of disparate data sources, wherein the data sources include a slot data system and a public internet source; compile the raw data into a structured dataset; train an artificial intelligence (AI) model on the structured dataset; execute an Asset Analyzer module that uses the trained AI model to analyze the structured dataset to generate a first recommendation for optimizing a casino gaming asset. The casino gaming asset is a multi-game multi-denomination (MGMD) machine and the Asset Analyzer module is further configured to; analyze performance of game combinations on the 2026202226   07 Aug 2026 MGMD machine; and generate the first recommendation that includes, at least, a recommendation to reconfigure the game combinations available on the MGMD machine. The system is further configured to execute a Player Reviewer module that uses the trained AI model to analyze player reviews collected from the public internet source to generate a second recommendation for improving player experience; and cause a presentation of the first and second recommendations on a graphical user interface.

[0009] A method and / or system for optimizing casino operations using artificial intelligence, is described in the present disclosure. The method and / or system are configured to perform operations that include collecting, via a data collector module, raw data from a plurality of disparate data sources. In some examples, the data sources include a casino management system, a hotel management system, and an online platform. The operations can also include compiling, via a data compiler, the raw data into a structured format. The operations can also include training, via an artificial intelligence (AI) training module, an AI model using the structured data. The operations can also include analyzing, via an Asset Analyzer module utilizing the trained AI model, casino asset data to identify an optimization for a casino asset. The optimization can include one of a physical relocation of the asset or a parameter reconfiguration of the asset. The operations can further include analyzing, via a Player Reviewer module utilizing the trained AI model, player review data from the online platform to determine a sentiment of the player review. The operations can further include generating, for display on a unified dashboard, a first recommendation based on the identified optimization for the casino asset and a second recommendation based on the determined sentiment of the player review.

[0010] Additional features and advantages of the disclosed subject matter are described in, and will be apparent from, the following detailed description and the accompanying drawings. Brief Description of the Drawings

[0011] FIG. 1 is a diagram of an example network according to one or more embodiments of the present disclosure.

[0012] FIG. 2 is a schematic view of a gaming system according to one or more embodiments of the present disclosure.

[0013] FIG. 3 is a diagram of a computer system according to one or more embodiments of the present disclosure. 2026202226   07 Aug 2026

[0014] FIG. 4 illustrates an example architecture of the disclosed solution according to one or more embodiments of the present disclosure.

[0015] FIG. 5 illustrates an example user interface of an Asset Analyzer module according to one or more embodiments of the present disclosure.

[0016] FIG. 6 illustrates an example user interface of a Player Review module according to one or more embodiments of the present disclosure.

[0017] FIG. 7 illustrates an example method flow according to one or more embodiments of the present disclosure.

[0018] The subject matter of the present disclosure is susceptible to various modifications and alternative forms. Specific embodiments have been shown by way of example in the drawings and are described in detail herein. It should be understood, however, that the present disclosure is not intended to be limited to the particular forms disclosed. Rather, the appended claims are intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the disclosure. Detailed Description

[0019] While the disclosed subject matter is susceptible of embodiment in many different forms, there is shown in the drawings, and will herein be described in detail, at least some embodiments with the understanding that the present disclosure is to be considered as an exemplification of the principles of the disclosed subject matter and is not intended to limit the broad aspects of the disclosure to the embodiments illustrated. For purposes of the present detailed description, the singular includes the plural and vice versa (unless specifically disclaimed); the words “and” and “or” shall be both conjunctive and disjunctive; the word “all” means “any and all”; the word “any” means “any and all”; and the word “including” means “including without limitation.”

[0020] FIG. 1 is a diagram of an example network ("network 100") according to one or more embodiments of the present disclosure. The network 100 includes a gaming platform system 140 communicatively coupled to a casino system 130 via one or more telecommunication networks (i.e., "telecommunication network(s) 160"). In some embodiments, the telecommunication network(s) 160 include, but are not limited to, the Internet, a computer network, a cell phone communication network, etc. In one embodiment, the gaming platform system 140 is hosted 2026202226   07 Aug 2026 within casino network 132. In other embodiments, the gaming platform system 140 may be a part of, or associated with, a global platform (e.g., to provide a scalable, unified infrastructure that enables cross-border interactions, worldwide accessibility, standardized experiences, integration of diverse services or applications, etc.), a data platform (e.g., an integrated set of technologies that enables acquisition, storage, preparation, delivery, and governance of data, as well as a security layer for users and applications), or a unified global data platform which combines aspects of both. The gaming platform system 140 incorporates an AI automation tool (e.g., AI tool 142). Additional examples of one or more AI automation tools used in association with one or more gaming systems, networks, etc. are described in United States Patent Application Serial No. 18 / 794,858 filed August 5, 2024 ("18 / 794,858 Application") and in United States Patent Application Serial No. 18 / 907,925 filed October 7, 2024 ("18 / 907,925 Application"), which 18 / 794,858 Application and 18 / 907,925 Application are each incorporated by reference herein in their respective entireties.

[0021] The gaming platform system 140 (e.g., via AI tool 142) is a specialized AI platform that leverages artificial intelligence to increase casino revenue and improve player experience. The solution integrates an Asset Analyzer module to optimize the performance of gaming assets and a Player Reviewer module to analyze customer feedback. The Asset Analyzer uses machine learning algorithms, including artificial neural networks and Apriori algorithms, to analyze data from various sources and predict revenue increases from specific asset optimizations. This analysis can include parameters such as coin-in, coin-out, hold percentage, number of bets, number of jackpots, jackpot amounts, and performance by specific time periods (e.g., peak performing hours) or physical groupings (e.g., zone or bank). It provides recommendations, such as moving a slot machine from a low-performing location to a high-performing one or reconfiguring multi-game combinations. The Player Reviewer module automatically gathers player reviews from online platforms using web scrapers and employs probabilistic classifiers, such as Naive Bayes and Support Vector Machine (SVM) algorithms, to perform sentiment analysis. The insights from both modules are presented on a unified dashboard, providing casino operators with a comprehensive, data-driven tool to make quick decisions, improve operational efficiency, and enhance the overall player experience.

[0022] In one embodiment, one of the additional systems or devices communicatively coupled to the gaming platform system 140 includes a casino system 130. In one embodiment, the casino 2026202226   07 Aug 2026 system 130 includes a gateway 120 (e.g., a demilitarized zone (DMZ) Server) gateway communicatively coupled via a gaming network, (e.g., via casino network 132)) to a player tracking system 135, which is communicatively coupled to a gaming device 110. The gateway 120 may be a server, a desktop computer, a laptop, a smartphone, a gaming machine, or other form of electronic device having one or more processors, a computer memory, an electronic communications system (e.g., a bus, a network interface device, a wireless communications device, etc.), etc. For instance, gateway 120 may be computer system 300 described in FIG. 3. The gaming device 110 includes player interface device 111 and game controller 112. One example of a gaming device 110 is gaming machine 310 described in FIG. 3. Another example of a gaming device 110 is a gaming table. In one example, player interface device 111 may connect to, or be associated with, input / output device(s) 254 and / or external-system interface 258. In another example, player interface device 111 may be a player interface device associated with a gaming table. Game controller 112 may be incorporated with game-logic circuitry 240. Presentation device(s) may be connected to, or associated with, output device(s) 252 and / or input / output devices 254 (e.g., for touch-screen devices). One example of the player interface device 111 includes the iView® player interface device manufactured by Light & Wonder, Inc, referred to herein as an “iView® player interface device,” “iView® product” or “iView® system”). The player interface device 111 may be communicatively connected to the gaming device 110 (e.g., connected via Universal Serial Bus (USB) connection). An example description of the iView® product can be found in United States (U.S.) Patent No. 8,241,123 to Kelly et al., the entirety of which is hereby incorporated by reference.

[0023] Player tracking system 135 is authorized to perform transactions with, and / or to securely communicate with, player interface device 111. In some embodiments, some combination of one or more of player interface device 111, player tracking system 135, gateway 120, and / or one or more data storage devices (e.g., local database(s)) may also be collectively referred to as a “player tracking system,” a “patron management system,” a “player tracking application server,” etc., or more generally as, or part of, the casino system 130. In some embodiments, the player tracking system 135 refers to a casino player tracking system (CPTS) or player-centric casino marketing system that provides one or more of, but not limited to, player data collection and analysis, player segmentation and targeting, loyalty program management, personalized marketing and promotions, player tracking and analytics, customer relationship 2026202226   07 Aug 2026 management (CRM), etc. An example of the player tracking system 135 is the CMP® playertracking product and / or the Elite Bonusing Suite® marketing product, both available by Light & Wonder, Inc. In some embodiments, the player tracking system integrates with a casino management system (CMS) 136. The CMS 136 provides (via player interface device 111) “system-based content” and / or “system-based services.” System-based content and / or systembased services may include, but are not necessarily limited to, content related to player benefits, casino services, marketing bonuses, promotions, advertisements, beverage or dining services, or any other information that is relevant to the player’s gaming experience other than the wagering game itself. Content for a wagering game may be referred to as game content. Game content, for instance, includes game assets of the wagering game, content related to a bet placed on the game (e.g., bet meters, pay tables, payout / collection, credit meters, number of lines selected for betting, an amount bet per line, a maximum bet, etc.), game play elements of the game (e.g., reels, indicia, game symbols,), game instructions, etc. The term “gaming content,” as used herein, comprises both system-based content and game content. Examples of the CMS 136 include, but are not limited to, one or more of the ACSC Casino Management System® product, the SDS® slotmanagement product, the Bally Unified Wallet® product, all available from Light & Wonder, Inc. In some embodiments, the player tracking system 135 can be incorporated into the CMS 136.

[0024] In one embodiment, the casino system 130 includes a gaming data aggregator 133 configured to aggregate data from various sources and / or to organize data obtained from the sources. In one embodiment, the gaming data aggregator 133 obtains gaming data from one or more databases associated with the casino system 130 (e.g., database(s) which store data related to players (e.g., stored in SQL or other relational type database), incidents, etc.). In one embodiment, the data is injected into one or more a machine learning (ML) models associated with AI tool 142.

[0025] The network 100 also includes one or more user computing devices associated with the casino system 130, such as mobile devices 102 and / or 104, used respectively by a player and / or a casino employee (e.g., mobile device 102 may be referred to herein as a player mobile device, mobile device 104 may be referred to herein as a casino employee mobile device). Mobile device 104 may be used by a dealer, or other operator employee, in connection with a table management system or application. 2026202226   07 Aug 2026

[0026] FIG. 2 is schematic view of a gaming system according to at least some aspects of the disclosed concepts. Referring to FIG. 2, a gaming machine 210 includes game-logic circuitry 240 (e.g., securely housed within a locked box inside a gaming cabinet). The game-logic circuitry 240 includes a central processing unit (CPU) 242 connected to a main memory 244 that comprises one or more memory devices. The CPU 242 includes any suitable processor(s), such as those made by Intel Corporation and Advanced Micro Devices, Inc. By way of example, the CPU 242 includes a plurality of microprocessors including a primary (e.g., master) processor, a secondary (e.g., worker, helper, etc.) processor, a parallel processor, etc. Game-logic circuitry 240, as used herein, comprises any combination of hardware, software, or firmware disposed in or outside of the gaming machine 210 that is configured to communicate with or control the transfer of data between the gaming machine 210 and a bus, another computer, processor, device, service, or network. The game-logic circuitry 240, and more specifically the CPU 242, comprises one or more controllers or processors and such one or more controllers or processors need not be disposed proximal to one another and may be located in different devices or in different locations. The game-logic circuitry 240, and more specifically main memory 244, comprises one or more memory devices which need not be disposed proximal to one another and may be located in different devices or in different locations. The game-logic circuitry 240 is operable to execute all of the various gaming methods and other processes disclosed herein. The main memory 244 includes a wagering-game unit 246. In one embodiment, the wagering-game unit 246 causes wagering games to be presented, such as video poker, video blackjack, video slots, video lottery, etc., in whole or part.

[0027] The game-logic circuitry 240 is also connected to an input / output (I / O) bus 248, which can include any suitable bus technologies, such as an AGTL+ frontside bus and a PCI backside bus. The I / O bus 248 is connected to various input devices 250, output devices 252, and input / output devices 254.

[0028] By way of example, the output devices 252 may include a primary presentation device, (e.g., primary display), a secondary presentation device, (e.g., a secondary display), and one or more audio speakers. The primary presentation device or the secondary presentation device may be a mechanical-reel display device, a video display device, or a combination thereof. In one such combination disclosed in U.S. Patent No. 6,517,433, a transmissive video display is disposed in front of the mechanical-reel display to portray a video image superimposed upon electromechanical reels. In another combination disclosed in U.S. Patent No. 7,654,899, a projector 2026202226   07 Aug 2026 projects video images onto stationary or moving surfaces. In yet another combination disclosed in U.S. Patent No. 7,452,276, miniature video displays are mounted to electro-mechanical reels and portray video symbols for the game. In a further combination disclosed in U.S. Patent No. 8,591,330, flexible displays such as OLED or e-paper displays are affixed to electro-mechanical reels. The aforementioned U.S. Patent Nos. 6,517,433, 7,654,899, 7,452,276, and 8,591,330 are incorporated herein by reference in their entireties.

[0029] The presentation devices, the audio speakers, lighting assemblies, and / or other devices associated with presentation are collectively referred to as a “presentation assembly” of the gaming machine 210. The presentation assembly may include one presentation device (e.g., the primary presentation device), some of the presentation devices of the gaming machine 210, or all of the presentation devices of the gaming machine 210. The presentation assembly may be configured to present a unified presentation sequence formed by visual, audio, tactile, and / or other suitable presentation means, or the devices of the presentation assembly may be configured to present respective presentation sequences or respective information.

[0030] The presentation assembly, and more particularly the primary presentation device and / or the secondary presentation device, variously presents information associated with wagering games, non-wagering games, community games, progressives, advertisements, services, premium entertainment, text messaging, emails, alerts, announcements, broadcast information, subscription information, etc. appropriate to the particular mode(s) of operation of the gaming machine 210. The gaming machine 210 may include a touch screen(s) mounted over the primary or secondary presentation devices, buttons on a button panel, a bill / ticket acceptor, a card reader / writer, a ticket dispenser, and player-accessible ports (e.g., audio output jack for headphones, video headset jack, USB port, wireless transmitter / receiver, etc.). It should be understood that numerous other peripheral devices and other elements exist and are readily utilizable in any number of combinations to create various forms of a gaming machine in accord with the present concepts.

[0031] The player input devices, such as the touch screen, buttons, a mouse, a joystick, a gesture-sensing device, a voice-recognition device, and a virtual-input device, accept player inputs and transform the player inputs to electronic data signals indicative of the player inputs, which correspond to an enabled feature for such inputs at a time of activation (e.g., pressing a “Max Bet” button or soft key to indicate a player’s desire to place a maximum wager to play the wagering 2026202226   07 Aug 2026 game). The inputs, once transformed into electronic data signals, are output to game-logic circuitry for processing. The electronic data signals are selected from a group consisting essentially of an electrical current, an electrical voltage, an electrical charge, an optical signal, an optical element, a magnetic signal, and a magnetic element.

[0032] The input / output devices 254 include one or more value input / payment devices and value output / payout devices. In order to deposit cash or credits onto the gaming machine 210, the value input devices are configured to detect a physical item associated with a monetary value that establishes a credit balance on a credit meter. The physical item may, for example, be currency bills, coins, tickets, vouchers, coupons, cards, and / or computer-readable storage mediums. The deposited cash or credits are used to fund wagers placed on the wagering game played via the gaming machine 210. Examples of value input devices include, but are not limited to, a coin acceptor, a bill / ticket acceptor (e.g., a bill validator), a card reader / writer, a wireless communication interface for reading cash or credit data from a nearby mobile device, and a network interface for withdrawing cash or credits from a remote account via an electronic funds transfer. In response to a cashout input that initiates a payout from the credit balance on the “credits” meter, the value output devices are used to dispense cash or credits from the gaming machine 210. The credits may be exchanged for cash at, for example, a cashier or redemption station. Examples of value output devices include, but are not limited to, a coin hopper for dispensing coins or physical gaming tokens (e.g., chips), a bill dispenser, a card reader / writer, a ticket dispenser for printing tickets redeemable for cash or credits, a wireless communication interface for transmitting cash or credit data to a nearby mobile device, and a network interface for depositing cash or credits to a remote account via an electronic funds transfer.

[0033] The I / O bus 248 is also connected to a storage unit 256 and an external-system interface 258, which is connected to external system(s) 260  (e.g., wagering-game networks, communications networks, etc.).

[0034] The external system(s) 260 includes, in various aspects, a gaming network, other gaming machines or terminals, a gaming server, a remote controller, communications hardware, or a variety of other interfaced systems or components, in any combination. In yet other aspects, the external system(s) 260 comprises a player’s portable electronic device (e.g., cellular phone, electronic wallet, etc.) and the external-system interface 258 is configured to facilitate wireless communication and data transfer between the portable electronic device and the gaming machine 2026202226   07 Aug 2026 210, such as by a near-field communication path operating via magnetic-field induction or a frequency-hopping spread spectrum RF signals (e.g., Bluetooth, etc.).

[0035] The gaming machine 210 optionally communicates with the external system(s) 260 such that the gaming machine 210 operates as a thin, thick, or intermediate client. The game-logic circuitry 240—whether located within (“thick client”), external to (“thin client”), or distributed both within and external to (“intermediate client”) the gaming machine 210—is utilized to provide a wagering game on the gaming machine 210. In general, the main memory 244 stores programming for a random number generator (RNG) and game-outcome logic. Furthermore, in some embodiments, the main memory stores at least some game content (e.g., art, sound, etc.) and / or dynamically generates game content that is approved or authorized for presentation (e.g., the game content has either (1) received regulatory approval from a gaming control board or commission and is verified by a trusted authentication program in the main memory 244 prior to game execution or (2) is dynamically generated via an artificial intelligence model, such as a machine learning model that is trained to generate content that is compliant with regulatory, or other, requirements). In one example, an authentication program generates a live authentication code (e.g., digital signature or hash) from the memory contents and compares it to a trusted code stored in the main memory 244. If the codes match, authentication is deemed a success, and the game is permitted to execute. If, however, the codes do not match, authentication is deemed a failure that must be corrected prior to game execution. Without this predictable and repeatable authentication, the gaming machine 210, external system(s) 260, or both are not allowed to perform or execute the RNG programming or game-outcome logic in a regulatory-approved manner and are therefore unacceptable for commercial use. In other words, through the use of the authentication program, the game-logic circuitry facilitates operation of the game in a way that a person making calculations or computations could not.

[0036] When a wagering-game instance is executed, the CPU 242 (comprising one or more processors or controllers) executes the RNG programming to generate one or more pseudo-random numbers. The pseudo-random numbers are divided into different ranges, and each range is associated with a respective game outcome. Accordingly, the pseudo-random numbers are utilized by the CPU 242 when executing the game-outcome logic to determine a resultant outcome for that instance of the wagering game. The resultant outcome is then presented to a player of the gaming machine 210 by accessing associated game assets, required for the resultant outcome, from the 2026202226   07 Aug 2026 main memory 244. The CPU 242 causes the game assets to be presented to the player as outputs from the gaming machine 210 (e.g., audio and video presentations). Instead of a pseudo-RNG, the game outcome may be derived from random numbers generated by a physical RNG that measures some physical phenomenon that is expected to be random and then compensates for possible biases in the measurement process. Whether the RNG is a pseudo-RNG or physical RNG, the RNG uses a seeding process that relies upon an unpredictable factor (e.g., human interaction of turning a key) and cycles continuously in the background between games and during game play at a speed that cannot be timed by the player, for example, at a minimum of 100Hz (100 calls per second) as set forth in Nevada’s New Gaming Device Submission Package. Accordingly, the RNG cannot be carried out manually by a human and is integral to operating the game.

[0037] The gaming machine 210 may be used to play centrally determined games. Centrally determined games are a type of game whose outcomes are determined by a central server and delivered to player terminals (e.g., to be displayed in an entertaining fashion). It includes, but is not limited to, Class 2 games, electronic pull-tab games, electronic scratch ticket games, historical horse racing, bingo games, etc. In an electronic pull-tab game, the RNG is used to randomize the distribution of outcomes in a pool and / or to select which outcome is drawn from the pool of outcomes when the player requests to play the game. In an electronic bingo game, the RNG is used to randomly draw numbers that players match against numbers printed on their electronic bingo card.

[0038] The gaming machine 210 may include additional peripheral devices or more than one of each component shown in FIG. 2. Any component of the gaming-machine architecture includes hardware, firmware, or tangible machine-readable storage media including instructions for performing the operations described herein. Machine-readable storage media includes any mechanism that stores information and provides the information in a form readable by a machine (e.g., gaming terminal, computer, etc.). For example, machine-readable storage media includes read only memory (ROM), random access memory (RAM), magnetic-disk storage media, optical storage media, flash memory, etc.

[0039] FIG. 3 is a block diagram of a computer system 300 according to one or more embodiments. The computer system 300 includes at least one processor 342 coupled to a chipset 344, as indicated in dashed lines. Also coupled to the chipset 344 are memory 346, a storage device 348, a keyboard 350, a graphics adapter 352, a pointing device 354, and a network adapter 356. A 2026202226   07 Aug 2026 display 358 is coupled to the graphics adapter 352. In one embodiment, the functionality of the chipset 344 is provided by a memory controller hub 360 and an I / O controller hub 362. In another embodiment, memory 346 is coupled directly to the processor 342 instead of to the chipset 344.

[0040] The storage device 348 is any non-transitory computer-readable storage medium, such as a hard drive, a compact disc read-only memory (CD-ROM), a DVD, or a solid-state memory device (e.g., a flash drive). Memory 346 holds instructions and data used by processor 342. The pointing device 354 may be a mouse, a track pad, a track ball, or another type of pointing device, and it is used in combination with the keyboard 350 to input data into the computer system 300. The graphics adapter 352 displays images and other information on the display 358. The network adapter 356 couples the computer system 300 to a local or wide area network.

[0041] As is known in the art, the computer system 300 can have different and / or other components than those shown in FIG. 3. In addition, the computer system 300 can lack certain illustrated components. In one embodiment, the computer system 300 acting as the gateway 120 (FIG. 1) may lack the keyboard 350, pointing device 354, graphics adapter 352, and / or display 358. Moreover, the storage device 348 can be local and / or remote from the computer system 300 (such as embodied within a storage area network (SAN)). Moreover, other input devices, such as, for example, touch screens may be included.

[0042] The network adapter 356 (may also be referred to herein as a communication device) may include one or more devices for communicating using one or more of the communication media and protocols discussed above with respect to FIG. 1, or FIG. 2.

[0043] In addition, some or all of the components of this general computer system 300 of FIG. 3 may be used as part of the processor and memory discussed above with respect to the systems or devices described in, or in relationship to, FIG. 1, FIG. 2, FIG. 4, FIG. 5, FIG. 6, or FIG. 7.

[0044] In some embodiments, a gaming system may comprise several such computer systems 300. The gaming system may include load balancers, firewalls, and various other components for assisting the gaming system to provide services to a variety of user devices. The computer system 300 is adapted to execute computer program modules for providing functionality described herein. As used herein, the term "module" refers to computer program logic utilized to provide the specified functionality. Thus, a module can be implemented in hardware, firmware, and / or software. In one embodiment, program modules are stored on storage device 348, loaded into memory 346, and executed by processor 342. 2026202226   07 Aug 2026

[0045] FIG. 4 illustrates an exemplary architecture 400 for the disclosed solution. The system is designed with a three-layer architecture: a data processing layer 403, an AI layer 409, and a UI layer 414. The process begins with a data collector 404, which gathers raw information from various data sources 402, such as SDS, CMP, and review data. This collected information is stored as raw data 406. A data compiler 408 then processes the raw data into a structured format. The structured data is passed to the AI layer 409, which contains an AI training module 410 that applies machine learning algorithms to the data. The resulting trained model and predictions are stored as trained data 412. The final UI layer 414 presents the data and recommendations to the user. This layer includes a main dashboard 416, an Asset Analyzer module 418, a Player Review module 420, and other modules 422. These other modules 422 may include, but are not limited to, a Promo module (e.g., for promotional data), a Player module (e.g., for player profile information), a Scheduler module (e.g., for configuring data collection jobs), an Audit module (e.g., for reviewing job history), a Tracker module (e.g., for monitoring recommendation outcomes), a Data module, an Admin module, and a Module Configuration module.

[0046] In at least some embodiments, the Tracker module, referenced in the other modules 422, is configured to monitor the implementation and results of recommendations accepted by a casino operator. For instance, if a user accepts a recommendation to move a slot machine, the tracker module can monitor the performance of that asset in its new location to verify the predicted revenue increase. The tracker module may compare performance metrics from before and after the change was implemented to track progress toward a goal. In some embodiments, while the performance outcome is tracked for reporting and verification, this outcome data is not automatically fed back to retrain the AI model 410; the model instead continues to be trained on new, real-time data from the data sources 402. In some embodiments, the Tracker Module tracks the completion of recommendations, displaying the status of completed items and a list of pending action items. The Tracker Module can further monitor the impact of the changes associated with the recommendations and provides insights based on the outcomes. The casino can then compare revenue changes across different time frames, game combinations, and seasonal patterns.

[0047] FIG. 5 illustrates an exemplary user interface 501 for the Asset Analyzer module. The interface displays information on best performing slots 530 and worst performing slots 532 across various metrics like average bet, total bet, win and “theo” bet (e.g., “theo” being an abbreviation for “theoretical,” such as average daily theoretical). A top performing games table 502 lists casino 2026202226   07 Aug 2026 assets by slot number, manufacturer, and location. The interface also includes a recommendation section 510, which may include a chart and text suggesting an action, such as moving a slot machine to a different location to increase revenue. Additionally, the interface includes an MGMD (multi-game multi-denomination) table 520 that analyzes the performance of different game combinations. This analysis is particularly useful for informing future game purchasing decisions and optimizing existing assets. The table 520 can show various rows for different MGMD game combinations, such as row 523, which specifies a first game name 524A (e.g., “Bonus 7 Wild Explosion’), a manufacturer 525 (e.g., “LNW”), a second game name 524B (e.g., Ultimate Fire Link), a location 526 (e.g., a location on a casino floor, such as location identified by identifier “AF01”), and an MGMD Percentage 522. The MGMD Percentage 522 may represent the percentage of total MGMD transactions that involved a specific game combination, thereby identifying popular pairings. Based on this analysis, a recommendation is provided to reconfigure certain games to make more revenue (e.g., “Reconfigure Bonus 7 Wild Explosion and Ultimate Fire Link to make more revenue”).

[0048] FIG. 6 illustrates an exemplary user interface 601 for the Player Review module. Within the player reviews section 600, a user can use a dropdown menu 602 to select a specific site. The interface then displays a sentiment analysis donut chart 604 providing an overview of player sentiment. This chart is divided into sections such amounts of detected positive sentiment 606 and amounts of detected negative sentiment 608. In one example, the chart can specify additional information about the detected positive and negative sentiments, such as Positive Correct Prediction (A), Positive Wrong Prediction (B), Negative Correct Prediction (C), and Negative Wrong Prediction (D). For example, in some embodiments, detected predictions can be checked for accuracy to determine whether the prediction was correct or wrong, such as to improve future predictions, to indicate accuracy ranges, etc. Below the main chart, the interface provides a time-based analysis graph 610 (e.g., for year-to-date graph) and a quarterly analysis graph 612, which show positive and negative sentiment trends over time.

[0049] FIG. 7 illustrates an example of a method flow ("flow 700") according to one or more embodiments of the present disclosure. In one example, flow 700 is for automating gamingspecific operations. The description of FIG. 7 refers to a "processor" that performs operations associated with flow 700. It should be noted that the reference to the processor may refer to the same physical processor or it may be one of a set of a plurality of processors. The set of processors 2026202226   07 Aug 2026 may operate in conjunction with each other and may be distributed across various networked devices, such as the local AI infrastructure, the one or more agent servers, the gaming terminals, or a user's client device. In one embodiment, the processor may be the central processing unit (CPU) 242 (see FIG. 2) or a processor in another device mentioned herein, such as the processor 342 associated with the computer 300.

[0050] Occasionally, the description of flow 700 may refer to FIG. 1 through FIG. 6 to describe various embodiments in a summarized manner.

[0051] Referring to FIG. 7, flow 700 begins at processing block 704, where a processor collects raw data. For example, the processor can collect the data as described in FIG. 1 and / or FIG. 4 (e.g., gaming data aggregator 133 aggregates gaming data, data collector 404 collects raw data 406, etc.).

[0052] Flow 700 continues at processing block 706, where the processor compiles the data. For example, the processor can compile data as described for data compiler 408 in FIG. 4.

[0053] Flow 700 continues at processing block 708, where the processor trains the AI model. For example, the processor trains the AI model using AI training module 410 (e.g., as described in FIG. 4, resulting in trained data 412).

[0054] The flow 700 then continues at processing block 710, where the processor determines whether to analyze asset data. If, at processing block 710, the processor determines to analyze asset data, then the flow 700 continues at processing block 712 where the processor generates asset recommendation. Examples of generating one or more asset recommendations are shown in FIG. 5.

[0055] After processing block 712 (if processor determines at processing block 710 to analyze asset data) or if at processing block 710 the processor determines to not analyze asset data, then the flow 700 continues at processing block 714 where the processor determines whether review data should be analyzed. If at processing block 714 the processor determines to analyze review data, the flow proceeds to processing block 716 where the processor generates review-based insights. Examples of generating review-based insights are shown in FIG. 6.

[0056] After processing block 716 (if processor determines at processing block 714 to analyze review data) or, if at processing block 714 the processor determines to not analyze review data, then the flow 700 continues at processing block 718 where the processor presents the outputs from the analyses for display on a unified dashboard. 2026202226   07 Aug 2026

[0057] The patent applications, patents, and printed publications cited herein are incorporated by reference in their entireties, except for any definitions, subject matter disclaimers or disavowals, and except to the extent that the incorporated material is inconsistent with the express disclosure herein, in which case the language in this disclosure controls.

[0058] The foregoing description of various embodiments has been provided for the purposes of illustration and description. It is not intended to be exhaustive or to limit the disclosure to the precise forms disclosed. The components and operations described herein may be implemented in hardware, software, or a combination thereof. Any of the features and variations described in the embodiments may be combined with any of the other features and variations described in other embodiments without limitation. Moreover, the operations described may be performed in any logical order, and in some implementations, certain operations may be optional.

[0059] The claims, and not the preceding summary or detailed description, define the scope of protection. Many modifications and variations are possible in light of the above teaching without departing from the broader aspects of the disclosure.

Claims

1. A method for optimizing casino operations using artificial intelligence, the methodcomprising:collecting, via a data collector module, raw data from a plurality of disparate data sources, wherein the data sources include a casino management system and an online platform;compiling, via a data compiler, the raw data into a structured format;training, via an artificial intelligence (AI) training module, an AI model using the structured data;analyzing, via an Asset Analyzer module utilizing the trained AI model, casino asset data to identify an optimization for a casino asset, wherein the optimization comprises a parameter reconfiguration of the asset, wherein the casino asset is a multigame multi-denomination (MGMD) machine, and the identified optimization is a recommendation to reconfigure a combination of games available on the MGMD machine;analyzing, via a Player Reviewer module utilizing the trained AI model, player review data from the online platform to determine a sentiment of the player review; andgenerating, for display on a unified dashboard, a first recommendation based on the identified optimization for the casino asset and a second recommendation based on the determined sentiment of the player review.

2. The method of claim 1,wherein in response to acceptance of the first recommendation, tracking, in a tracker module, an implementation status and a performance outcome of the first recommendation.

3. The method of either claim 1 or 2, wherein analyzing the casino asset data comprisesusing an artificial neural network to analyze slot machine master details including coin-in, coin-out, and hold percentage.2026202226   07 Aug 20264.     The method of any one of the preceding claims, wherein the identified optimizationfurther comprises a recommendation to move a first slot machine from a first location to a second location to increase revenue.

5. The method of any one of the preceding claims, wherein analyzing the player review datacomprises:extracting the player review data from the online platform using a web scraping tool; andclassifying the player review data as having a positive sentiment or a negative sentiment using a probabilistic classifier.

6. The method of claim 5, wherein the probabilistic classifier is one of a Naive Bayesclassifier or a Support Vector Machine (SVM) classifier.

7. A system for optimizing casino operations, the system comprising:a processor; anda memory storing instructions that, when executed by the processor, cause the system to: collect raw data from a plurality of disparate data sources, wherein the data sources include a slot data system and a public internet source;compile the raw data into a structured dataset;train an artificial intelligence (AI) model on the structured dataset;execute an Asset Analyzer module that uses the trained AI model to analyze the structured dataset to generate a first recommendation for optimizing a casino gaming asset,wherein the casino gaming asset is a multi-game multi-denomination (MGMD) machine and the Asset Analyzer module is further configured to:analyze performance of game combinations on the MGMD machine; andgenerate the first recommendation that includes, at least, a recommendation to reconfigure the game combinations available on the MGMD machine;2026202226   07 Aug 2026execute a Player Reviewer module that uses the trained AI model to analyze player reviews collected from the public internet source to generate a second recommendation for improving player experience; andcause a presentation of the first and second recommendations on a graphical user interface.

8. The system of claim 7, wherein the instructions further cause the system to:in response to acceptance of the first recommendation, execute a tracker module configured to monitor a performance metric associated with the first recommendation.

9. The system of either claim 7 or 8, wherein the Asset Analyzer module is configured touse an artificial neural network to analyze performance of slot machines and generate the first recommendation, wherein the first recommendation further comprises specifying moving a slot machine between two physical locations.

10. The system of any one of claims 7 to 9, wherein the Player Reviewer module is configured to:utilize a web scraper to extract player review text from the public internet source; andapply a sentiment analysis algorithm to classify the player review text as positive or negative.

11. The system of claim 10, wherein the sentiment analysis algorithm is a Naive Bayes classifier or a Support Vector Machine (SVM) classifier.

12. The system of any one of claims 7 to 11, wherein the graphical user interface is a unified dashboard that displays an output of the Asset Analyzer module and an output of the Player Reviewer module.2026202226   07 Aug 202613. A program that, when executed by a processor of a system for optimizing casino operations, causes the processor to perform the method of any one of claims 1 to 6.

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